Conclusions: the future of antimicrobial therapy - Augmentin and beyond

Relevance of the Consensus Principles for Appropriate Antibiotic Prescribing in 2022

Background

In the late 1990s, as a response to rising antimicrobial resistance (AMR), an independent multinational, interdisciplinary group was formed specifically targeting primary care antibiotic prescribing for community-acquired respiratory tract infections (CA-RTIs). The group comprised senior clinicians from Canada, Israel, Spain, Sweden, UK and USA. The group’s objectives were to provide recommendations for antibiotic stewardship in the community because, whilst it was widely accepted that inappropriate antibiotic use was contributing to AMR, it remained difficult to change prescribing behaviour. The group aimed to identify principles underlying appropriate antibiotic prescribing and guideline formulation to reduce morbidity from CA-RTIs, limit therapeutic failure and, importantly, curb AMR emergence. The group published a report in 2002, which has become known as the Consensus Principles.

Objectives

(i) To consider the relevance of the Consensus Principles in 2022 by reviewing current global approaches to rising AMR. A wide range of factors, such as antibiotic overuse, most recently seen in COVID-19 patients, are still driving rising AMR even though there has been a high-level international response to the AMR threat; and (ii) as an introduction to this Supplement, which reports the findings of analyses of how AMR is being addressed in nine disparate countries (Brazil, India, Kuwait, Mexico, Pakistan, Russia, Saudi Arabia, Türkiye and Vietnam). Understanding how these initiatives are being pursued in different countries helps identify areas where more information is needed.

Conclusions

Adherence to the Consensus Principles remains as important now as it was in 2002. Achieving appropriate antibiotic prescribing is a vital objective in order that the right patient receives the right antibiotics at the right time to ensure optimal clinical outcomes while at the same time helping to limit further increases in AMR.

Human Milk Oligosaccharides (HMOs) Sensitize Group B Streptococcus to Clindamycin, Erythromycin, Gentamicin, and Minocycline on a Strain Specific Basis

Human milk oligosaccharides (HMOs) possess antimicrobial and antibiofilm activity against Group B Streptococcus (GBS). HMOs were screened for their ability to potentiate antibiotic activity. We observed that HMOs potentiate the function of aminoglycosides, lincosamides, macrolides, and tetracyclines on a strain specific basis but not β-lactams or glycopeptides that inhibit cell wall synthesis. These findings are notable as GBS has evolved high levels of resistance toward aminoglycosides, macrolides, and tetracyclines. Finally, HMOs potentiate the function of aminoglycosides against both Staphylococcus aureus and Acinetobacter baumannii. On the basis of these observations, we hypothesized that HMOs act by increasing membrane permeability. This hypothesis was evaluated using a bacterial membrane permeability assay which revealed that HMOs increase membrane permeability toward propidium iodide.

Total Syntheses of Bulgecins A, B, and C and Their Bactericidal Potentiation of the β-Lactam Antibiotics

The bulgecins are iminosaccharide secondary metabolites of the Gram-negative bacterium Paraburkholderia acidophila and inhibitors of lytic transglycosylases of bacterial cell-wall biosynthesis and remodeling. The activities of the bulgecins are intimately intertwined with the mechanism of a cobiosynthesized β-lactam antibiotic. β-Lactams inhibit the penicillin-binding proteins, enzymes also critical to cell-wall biosynthesis. The simultaneous loss of the lytic transglycosylase (by bulgecin) and penicillin-binding protein (by β-lactams) activities results in deformation of the septal cell wall, observed microscopically as a bulge preceding bacterial cell lysis. We describe a practical synthesis of the three naturally occurring bulgecin iminosaccharides and their mechanistic evaluation in a series of microbiological studies. These studies identify potentiation by the bulgecin at subminimum inhibitory concentrations of the β-lactam against three pathogenic Gram-negative bacteria and establish for the first time that this potentiation results in a significant increase in the bactericidal efficacy of a clinical β-lactam.

Antibiotic Hybrids: the Next Generation of Agents and Adjuvants against Gram-Negative Pathogens?

The global incidence of drug-resistant Gram-negative bacillary infections has been increasing, and there is a dire need to develop novel strategies to overcome this problem. Intrinsic resistance in Gram-negative bacteria, such as their protective outer membrane and constitutively overexpressed efflux pumps, is a major survival weapon that renders them refractory to current antibiotics. Several potential avenues to overcome this problem have been at the heart of antibiotic drug discovery in the past few decades. We review some of these strategies, with emphasis on antibiotic hybrids either as stand-alone antibacterial agents or as adjuvants that potentiate a primary antibiotic in Gram-negative bacteria. Antibiotic hybrid is defined in this review as a synthetic construct of two or more pharmacophores belonging to an established agent known to elicit a desired antimicrobial effect. The concepts, advances, and challenges of antibiotic hybrids are elaborated in this article. Moreover, we discuss several antibiotic hybrids that were or are in clinical evaluation. Mechanistic insights into how tobramycin-based antibiotic hybrids are able to potentiate legacy antibiotics in multidrug-resistant Gram-negative bacilli are also highlighted. Antibiotic hybrids indeed have a promising future as a therapeutic strategy to overcome drug resistance in Gram-negative pathogens and/or expand the usefulness of our current antibiotic arsenal.

Multidrug evolutionary strategies to reverse antibiotic resistance

Antibiotic treatment has two conflicting effects: the desired, immediate effect of inhibiting bacterial growth and the undesired, long-term effect of promoting the evolution of resistance. Although these contrasting outcomes seem inextricably linked, recent work has revealed several ways by which antibiotics can be combined to inhibit bacterial growth while, counterintuitively, selecting against resistant mutants. Decoupling treatment efficacy from the risk of resistance can be achieved by exploiting specific interactions between drugs, and the ways in which resistance mutations to a given drug can modulate these interactions or increase the sensitivity of the bacteria to other compounds. Although their practical application requires much further development and validation, and relies on advances in genomic diagnostics, these discoveries suggest novel paradigms that may restrict or even reverse the evolution of resistance.

Bacterial responses to antibiotics and their combinations

Antibiotics affect bacterial cell physiology at many levels. Rather than just compensating for the direct cellular defects caused by the drug, bacteria respond to antibiotics by changing their morphology, macromolecular composition, metabolism, gene expression and possibly even their mutation rate. Inevitably, these processes affect each other, resulting in a complex response with changes in the expression of numerous genes. Genome-wide approaches can thus help in gaining a comprehensive understanding of bacterial responses to antibiotics. In addition, a combination of experimental and theoretical approaches is needed for identifying general principles that underlie these responses. Here, we review recent progress in our understanding of bacterial responses to antibiotics and their combinations, focusing on effects at the levels of growth rate and gene expression. We concentrate on studies performed in controlled laboratory conditions, which combine promising experimental techniques with quantitative data analysis and mathematical modeling. While these basic research approaches are not immediately applicable in the clinic, uncovering the principles and mechanisms underlying bacterial responses to antibiotics may, in the long term, contribute to the development of new treatment strategies to cope with and prevent the rise of resistant pathogenic bacteria.

A lack of synergy between membrane-permeabilizing cationic antimicrobial peptides and conventional antibiotics

The rapid rise in morbidity and mortality from drug-resistant pathogenic bacteria has generated elevated interest in combination therapy using antimicrobial agents. Antimicrobial peptides (AMPs) are a candidate drug class to advance the development of combination therapies. Although the literature is ambiguous, the generic membrane disrupting activity of AMPs could enable them to synergize with conventional small molecule antibiotics by increasing access to the cell and by triggering membrane damage mediators. We used a novel assay to measure interactions, expressed as fractional inhibitory concentration (FIC), between four conventional antibiotics in combination with four well-characterized, membrane permeabilizing AMPs, against three species of Gram negative and Gram positive bacteria, giving 40 total pair-wise measurements of FIC with statistical uncertainties. We chose a set of AMPs that are known to dramatically disrupt the membranes of both Gram negative and Gram positive bacteria. Yet none of the membrane permeabilizing antimicrobial peptides interacted synergistically with any of the conventional antibiotic drugs in any organism. Large-scale membrane disruption and permeabilization by AMPs is not sufficient to drive them to act synergistically with chemical antibiotics in either Gram negative or Gram positive microbes.

Use of collateral sensitivity networks to design drug cycling protocols that avoid resistance development

New drug deployment strategies are imperative to address the problem of drug resistance, which is limiting the management of infectious diseases and cancers. We evolved resistance in Escherichia coli toward 23 drugs used clinically for treating bacterial infections and mapped the resulting collateral sensitivity and resistance profiles, revealing a complex collateral sensitivity network. On the basis of these data, we propose a new treatment framework--collateral sensitivity cycling--in which drugs with compatible collateral sensitivity profiles are used sequentially to treat infection and select against drug resistance development. We identified hundreds of such drug sets and demonstrated that the antibiotics gentamicin and cefuroxime can be deployed cyclically such that the treatment regimen selected against resistance to either drug. We then validated our findings with related bacterial pathogens. These results provide proof of principle for collateral sensitivity cycling as a sustainable treatment paradigm that may be generally applicable to infectious diseases and cancer.

Contribution of mathematical modeling to the fight against bacterial antibiotic resistance

PURPOSE OF REVIEW

Modeling of antibiotic resistance in pathogenic bacteria responsible for human disease has developed considerably over the last decade. Herein, we summarize the main published studies to illustrate the contribution of models for understanding both within-host and population-based phenomena. We then suggest possible topics for future studies.

RECENT FINDINGS

Model building of bacterial resistance has involved epidemiologists, biologists and modelers with two different objectives. First, modeling has helped largely in identifying and understanding the factors and biological phenomena responsible for the emergence and spread of resistant strains. Second, these models have become important decision support tools for medicine and public health.

SUMMARY

Major improvements of models in the coming years should take into account specific pathogen characteristics (resistance mechanisms, multiple colonization phenomena, cooperation and competition among species) and better description of the contacts associated with transmission risk within populations.

Antibiotic dose impact on resistance selection in the community: a mathematical model of beta-lactams and Streptococcus pneumoniae dynamics

Streptococcus pneumoniae is a major pathogen in the community and presents high rates of resistance to the available antibiotics. To prevent antibiotic treatment failure caused by highly resistant bacteria, increasing the prescribed antibiotic dose has recently been suggested. The aim of the present study was to assess the influence of beta-lactam prescribed doses on the emergence of resistance and selection in the community. A mathematical model was constructed by combining S. pneumoniae pharmacodynamic and population-dynamic approaches. The received-dose heterogeneity in the population was specifically modeled. Simulations over a 50-year period were run to test the effects of dose distribution and antibiotic exposure frequency changes on community resistance patterns, as well as the accuracy of the defined daily dose as a predictor of resistance. When the frequency of antibiotic exposure per year was kept constant, dose levels had a strong impact on the levels of resistance after a 50-year simulation. The lowest doses resulted in a high prevalence of nonsusceptible strains (> or =70%) with MICs that were still low (1 mg/liter), whereas high doses resulted in a lower prevalence of nonsusceptible strains (<40%) and higher MICs (2 mg/liter). Furthermore, by keeping the volume of antibiotics constant in the population, different patterns of use (low antibiotic dose and high antibiotic exposure frequency versus high dose and low frequency) could lead to markedly different rates of resistance distribution and prevalence (from 10 to 100%). Our results suggest that pneumococcal resistance patterns in the community are strongly related to the individual beta-lactam doses received: limiting beta-lactam use while increasing the doses could help reduce the prevalence of resistance, although it should select for higher levels of resistance. Surveillance networks are therefore encouraged to collect both daily antibiotic exposure frequencies and individual prescribed doses.

Novel approaches to discovery of antibacterial agents

Antimicrobial resistance is a rapidly increasing problem impacting the successful treatment of bacterial infectious disease. To combat resistance, the development of new treatment options is required. Recent advances in technology have aided in the discovery of novel antibacterial agents, specifically through genome mining for novel natural product biosynthetic gene clusters and improved small molecule high-throughput screening methods. Novel targets such as lipopolysaccharide and fatty acid biosyntheses have been identified by essential gene studies, representing a shift from traditional antibiotic targets. Finally, inhibiting non-essential genes with small molecules is being explored as a method for rescuing the activity of ‘old’ antibiotics, providing a novel synergistic approach to antimicrobial discovery.